Numerical study on ocean response to storm in Arctic Ocean

2020 ◽  
Author(s):  
Hailun He ◽  
Long Lin
Keyword(s):  
Arctic Ocean ◽  
Mixed Layer ◽  
Initial Conditions ◽  
Numerical Study ◽  
Surface Current ◽  
Ocean Model ◽  
Storm Events ◽  
Ocean Response ◽  
Freshwater Fluxes ◽  
Storm Condition

<p>A one-column ocean model was used to study the ocean response to storm in Arctic Ocean. We design a number of idealized experiments by different surface forcing and initial condition. The results show the phenomena of mixed-layer extension during the storm events. The intensification of surface current reflects the momentum flux injected from wind and ice movement. Furthermore, by changing the surface heat and freshwater fluxes, the dependences of mixed-layer variation on surface forcing are discussed. Finally, the numerical tests on different initial conditions show how the pre-storm condition affects the ocean response to storm. The results therefore reveal the dependence of mixed-layer extension on the initial stratification.</p>

scholarly journals Impacts of Oceanic Preexisting Conditions on Predictions of Typhoon Hai-Tang in 2005

2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Akiyoshi Wada ◽  
Norihisa Usui
Keyword(s):  
Mixed Layer ◽  
Initial Conditions ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Central Pressure ◽  
Surface Cooling ◽  
Heat Potential ◽  
Spiral Rainbands ◽  
The Impact ◽  
Preexisting Conditions

We investigated the impact of variations in oceanic preexisting conditions on predictions of Typhoon Hai-Tang (2005) by using a coupled atmosphere-ocean model with 6-km horizontal resolution and providing the oceanic initial conditions on 12 July from 1997 to 2005 to the model. Variations in oceanic preexisting conditions caused variation in predicted central pressure of nearly 18 hPa at 72 h, whereas sea-surface cooling (SSC) induced by Hai-Tang caused a predicted central pressure difference of about 40 hPa. Warm-core oceanic eddies up to a few hundred kilometers across and a deep mixed layer climatologically distributed in the western North Pacific led to high mixed-layer heat potential, which increased latent heat flux, water vapor, and liquid water contents around Hai-Tang's center. These increases were closely associated with Hai-Tang's intensification. SSC negatively affected the eyewall, whereas variations in oceanic preexisting conditions remarkably affected spiral rainbands and the magnitude of SSC.

scholarly journals Numerical Study of the Effects of Wave-Induced Forcing on Dynamics in Ocean Mixed Layer

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Zengan Deng ◽  
Lian Xie ◽  
Ting Yu ◽  
Suixiang Shi ◽  
Jiye Jin ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Mixed Layer ◽  
Numerical Study ◽  
Mixed Layer Depth ◽  
Ocean Model ◽  
Stokes Drift ◽  
Current Transport ◽  
Hybrid Coordinate Ocean Model ◽  
Stokes Transport ◽  
Wave Induced

Numerical experiments using hybrid coordinate ocean model (HYCOM) are designed to quantify the effects of wind wave-induced Coriolis-Stokes forcing (CSF) on mixed layer (ML) dynamics in a global context. CSF calculated by the wave parameters simulated by using the WaveWatch III (WW3) model is introduced as a new driving force for HYCOM. The results show that noticeable influence on ocean circulation in ML can be caused by CSF. Over most of the global oceans the direction of Stokes transport is different from that of the change in current transport caused by CSF. This is not unusual because CSF is normal to Stokes drift. However, the CSF-caused change in current transport and the wave-induced Stokes transport have the same magnitude. The seasonal variabilities of mixed layer temperature (MLT) and mixed layer depth (MLD) caused by CSF are analyzed, and the possible relationship between them is also given.

Mixed Layer Models and Their Application to Water Quality Problems

1994 ◽  
Vol 29 (2-3) ◽  
pp. 221-232
Author(s):  
M.J. McCormick
Keyword(s):  
Water Quality ◽  
Mixed Layer ◽  
Thermal Structure ◽  
Mass Conservation ◽  
Eddy Diffusion ◽  
Rate Of Change ◽  
Surface Mixed Layer ◽  
Storm Events ◽  
Quality Model ◽  
Mixing Processes

Abstract Four one-dimensional models which have been used to characterize surface mixed layer (ML) processes and the thermal structure are described. Although most any model can be calibrated to mimic surface water temperatures, it does not imply that the corresponding mixing processes are well described. Eddy diffusion or "K" models can exhibit this problem. If a ML model is to be useful for water quality applications, then it must be able to resolve storm events and, therefore, be able to simulate the ML depth, h, and its time rate of change, dh/dt. A general water quality model is derived from mass conservation principles to demonstrate how ML models can be used in a physically meaningful way to address water quality issues.

scholarly journals Numerical Study on the Expansion and Variation of Changjiang Diluted Water in Summer and Autumn

2021 ◽  
Vol 9 (3) ◽  
pp. 317
Author(s):  
Wanli Hou ◽  
Menglin Ba ◽  
Jie Bai ◽  
Jianghua Yu
Keyword(s):  
Yangtze River ◽  
Sea Water ◽  
Numerical Study ◽  
River Estuary ◽  
Ocean Model ◽  
Theoretical Research ◽  
Yangtze River Estuary ◽  
Hydrodynamic Characteristics ◽  
Changjiang Diluted Water ◽  
Transportation Route

In view of the expansion and directional change mechanisms of Yangtze River water diluted with sea water in the shelf region (also known as Changjiang diluted water [CDW]) during summer and autumn, a three-dimensional hydrodynamic model of the Yangtze River Estuary (YRE) and its adjacent waters was established based on the Finite Volume Community Ocean Model (FVCOM). Compared with the measured data, the model accurately simulates the hydrodynamic characteristics of the YRE. On that basis, the influence of the expansion patterns of the CDW in both summer and autumn was studied. It was found that, in 2019, the CDW expanded to the northeast in the summer and to the southeast in the autumn, and that the route of the CDW is mainly controlled by the wind, not the runoff. Current seasonal winds also change the transportation route of the CDW by affecting its hydrodynamic field. Typhoons are frequent in both summer and autumn, causing abnormalities in both the transportation route and expansion of the CDW. During a typhoon, a large amount of the CDW is transported in a continuous and abnormal manner, accelerating the path turning of the CDW. This paper enhances the existing theoretical research of the CDW and provides a reference with respect to the expansion of diluted water all over the world.

scholarly journals Ensemble forecasting greatly expands the prediction horizon for ocean mesoscale variability

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Prasad G. Thoppil ◽  
Sergey Frolov ◽  
Clark D. Rowley ◽  
Carolyn A. Reynolds ◽  
Gregg A. Jacobs ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Mesoscale Dynamics ◽  
Predictive Skill ◽  
Freshwater Transport ◽  
Prediction Horizon ◽  
Initial Location ◽  
Ocean Models ◽  
High Uncertainty

AbstractMesoscale eddies dominate energetics of the ocean, modify mass, heat and freshwater transport and primary production in the upper ocean. However, the forecast skill horizon for ocean mesoscales in current operational models is shorter than 10 days: eddy-resolving ocean models, with horizontal resolution finer than 10 km in mid-latitudes, represent mesoscale dynamics, but mesoscale initial conditions are hard to constrain with available observations. Here we analyze a suite of ocean model simulations at high (1/25°) and lower (1/12.5°) resolution and compare with an ensemble of lower-resolution simulations. We show that the ensemble forecast significantly extends the predictability of the ocean mesoscales to between 20 and 40 days. We find that the lack of predictive skill in data assimilative deterministic ocean models is due to high uncertainty in the initial location and forecast of mesoscale features. Ensemble simulations account for this uncertainty and filter-out unconstrained scales. We suggest that advancements in ensemble analysis and forecasting should complement the current focus on high-resolution modeling of the ocean.

Coupled Sea Ice-Ocean Model of the Arctic Ocean

1998 ◽  
Vol 120 (2) ◽  
pp. 77-84 ◽  
Author(s):  
I. V. Polyakov ◽  
I. Yu. Kulakov ◽  
S. A. Kolesov ◽  
N. Eu. Dmitriev ◽  
R. S. Pritchard ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Three Dimensional ◽  
Coupled Model ◽  
Ocean Model ◽  
Distribution Functions ◽  
Constitutive Law ◽  
Prognostic Models ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Ocean Layer

A fully prognostic coupled ice-ocean model is described. The ice model is based on the elastic-plastic constitutive law with ice mass and compactness described by distribution functions. The ice thermodynamics model is applied individually to each ice thickness category. Advection of the ice partial mass and concentrations is parameterized by a fourth-order algorithm that conserves monotonicity of the solution. The ocean is described as a three-dimensional time-dependent baroclinic model with free surface. The coupled model is applied to establish the Arctic Ocean seasonal climatology using fully prognostic models for ice and ocean. Results reflect the importance of the ice melting/freezing in the formation of the thermohaline structure of the upper ocean layer.

scholarly journals Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Extent ◽  
Pacific Side ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

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